Article: Bio-inspired polymer array vapor sensor with dual signals of fluorescence intensity and wavelength shift.
Frontiers in bioengineering and biotechnology
2022 Volume 10, Page(s) 1058404
Abstract: Organic vapor sensors based on polymer owing to their tunable molecular structures and designable functions have attracted considerable research interest. However, detecting multiple organic vapors with high accuracy and a low detection limit is still ... ...
| Abstract | Organic vapor sensors based on polymer owing to their tunable molecular structures and designable functions have attracted considerable research interest. However, detecting multiple organic vapors with high accuracy and a low detection limit is still challenging. Herein, inspired by the mammalian olfactory recognition system, organic vapor sensors based on one-dimensional microfilament array structures with a wide range of sensing gases are demonstrated. By introducing aggregation-induced emission (AIE) molecules, sensors possess dual-optical sensing mechanisms of variation in fluorescence intensity and wavelength. By virtue of the synergistic effects of dual signals, superb accuracy and incredibly low detection limit are achieved for identifying analytes. In particular, the polymer/AIE microfilament array can detect acetone vapor down to 0.03% of saturated vapor pressure. In the saturated vapor of acetone, the fluorescence intensity of the sensor arrays was reduced by 53.7%, while the fluorescence wavelength was red-shifted by 21 nm. Combined with the principal component analysis (PCA) algorithm, the polymer/AIE molecular sensor arrays accomplished the classification and identification of acetone, ethanol, methylene chloride, toluene, and benzene. This bioinspired approach with dual sensing signals may broaden practical applications to high-performance gas sensors for precise molecular detection. |
|---|---|
| Language | English |
| Publishing date | 2022-10-31 |
| Publishing country | Switzerland |
| Document type | Journal Article |
| ZDB-ID | 2719493-0 |
| ISSN | 2296-4185 |
| ISSN | 2296-4185 |
| DOI | 10.3389/fbioe.2022.1058404 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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